In vivo behavior of nanoparticles

In biomedical research, various nanoparticles (NPs) are being developed for clinical applications ranging from diagnostics to therapy, utilizing their unique physicochemical properties as well as their high versatility. For each application it is essential that the NPs efficiently reach their target site in the body, for example, a specific cell type or substructure within an organ. Hence, the aim of this thesis was to study the microdistribution of quantum dots (QDs) in muscle tissue of healthy mice. To investigate the influence of surface modifications on the tissue distribution, QDs with either a polyethylene glycol (PEG) or a carboxyl surface coating were applied. Chapter 2 [Nekolla et al., 2016] demonstrates by means of in vivo real-time fluorescence microscopy, particle tracking, and transmission electron microscopy that the microdistribution of QDs is strongly influenced by their respective surface modification. Locally injected carboxyl QDs preferentially bind to constituents of the extracellular matrix, such as collagen fibers and basement membranes. Furthermore, carboxyl QDs are localized in caveolae of endothelial cells as well as in endothelial junctions, enabling them to translocate into the vessel lumen. In contrast, PEG QDs show little interaction with tissue components, but mainly diffuse in the interstitial space. The data suggest that constituents of the extracellular matrix act as a selective barrier depending on the QD surface modification. Chapter 3 [Rehberg, Nekolla et al., 2016] shows that immune cells play a part in the microdistribution of NPs in the tissue. By intraarterial injection of carboxyl QDs it was demonstrated that perivascular and tissue-resident macrophages are interconnected by microtubule-containing tubular membranous structures, so-called membrane nanotubes (MNTs). Inside these MNTs, carboxyl QDs are exclusively contained in vesicles, which are transported along the microtubules by molecular motors. Taken together, this thesis elucidates the extra-, intra-, and intercellular distribution of QDs at the microscopic tissue scale. The choice of surface modification critically influences the microdistribution, which should be considered for the future design of NPs that are intended for the use in biomedical applications. Furthermore, it is important to keep in mind that the distribution of NPs in the tissue takes place via different routes including the transport via networks of cells interconnected by MNTs.In der biomedizinischen Forschung werden diverse Nanopartikel (NP) für klinische Anwendungen, die von Diagnostik bis Therapie reichen, entwickelt. Dabei werden die einzigartigen physikalisch-chemischen Eigenschaften sowie die große Vielseitigkeit der NP genutzt. Für jede Anwendung ist es essentiell, dass die NP im Körper ihr Ziel erreichen, z.B. einen bestimmten Zelltyp oder eine spezifische Unterstruktur in einem Organ. Daher war das Ziel dieser Dissertation, die Mikrodistribution von Quantenpunkten (quantum dots, QDs) in Muskelgewebe von gesunden Mäusen zu untersuchen. Um den Einfluss der Oberflächenmodifikation auf die Verteilung im Gewebe zu erforschen, wurden QDs mit Polyethylenglycol (PEG)- oder Carboxyl- Oberflächengruppen verwendet. Kapitel 2 [Nekolla et al., 2016] zeigt mit Hilfe von Echtzeit-Fluoreszenzmikroskopie, Partikel-Tracking und Transmissionselektronenmikroskopie, dass die Mikrodistribution von QDs stark von der Oberflächenmodifikation beeinflusst wird. Lokal injizierte Carboxyl-QDs binden an Elemente der Extrazellulärmatrix wie Kollagenfasern und Basalmembranen. Darüberhinaus befinden sich Carboxyl-QDs in endothelialen Caveolae sowie in Zell-Zell-Kontakten zwischen Endothelzellen, was die Translokation in das Gefäßlumen erlaubt. Im Gegensatz dazu tritt nur wenig Interaktion zwischen PEG-QDs und Gewebekomponenten auf, vielmehr diffundieren PEG-QDs hauptsächlich im Interstitium. Die Daten deuten darauf hin, dass Bestandteile der Extrazellulärmatrix je nach QD-Oberflächenmodifikation als selektive Barriere wirken. Kapitel 3 [Rehberg, Nekolla et al., 2016] legt dar, dass Immunzellen einen Anteil an der Mikrodistribution von NP im Gewebe haben. Mithilfe von intraarterieller Injektion von Carboxyl-QDs wurde gezeigt, dass perivaskuläre und gewebsständige Makrophagen durch röhrenförmige Membranstrukturen, sog. membrane nanotubes (MNTs), die Mikrotubuli enthalten, verbunden sind. Carboxyl-QDs befinden sich in den MNTs ausschließlich in Vesikeln, die mit Hilfe von molekularen Motoren entlang der Mikrotubuli transportiert werden. Zusammengefasst erläutert diese Dissertation die extra-, intra- und interzelluläre Verteilung von QDs auf der mikroskopischen Gewebeebene. Die Wahl der Oberflächenmodifikation hat einen entscheidenden Einfluss auf die Mikrodistribution. Dies sollte für die zukünftige Entwicklung von NP für biomedizinische Anwendungen bedacht werden. Darüberhinaus ist es wichtig zu berücksichtigen, dass NP im Gewebe auf unterschiedliche Art und Weise verteilt werden. Dazu zählt auch der Transport in Netzwerken von Zellen, die durch MNTs verbunden sind

In vivo behavior of nanoparticles

In biomedical research, various nanoparticles (NPs) are being developed for clinical applications ranging from diagnostics to therapy, utilizing their unique physicochemical properties as well as their high versatility. For each application it is essential that the NPs efficiently reach their target site in the body, for example, a specific cell type or substructure within an organ. Hence, the aim of this thesis was to study the microdistribution of quantum dots (QDs) in muscle tissue of healthy mice. To investigate the influence of surface modifications on the tissue distribution, QDs with either a polyethylene glycol (PEG) or a carboxyl surface coating were applied. Chapter 2 [Nekolla et al., 2016] demonstrates by means of in vivo real-time fluorescence microscopy, particle tracking, and transmission electron microscopy that the microdistribution of QDs is strongly influenced by their respective surface modification. Locally injected carboxyl QDs preferentially bind to constituents of the extracellular matrix, such as collagen fibers and basement membranes. Furthermore, carboxyl QDs are localized in caveolae of endothelial cells as well as in endothelial junctions, enabling them to translocate into the vessel lumen. In contrast, PEG QDs show little interaction with tissue components, but mainly diffuse in the interstitial space. The data suggest that constituents of the extracellular matrix act as a selective barrier depending on the QD surface modification. Chapter 3 [Rehberg, Nekolla et al., 2016] shows that immune cells play a part in the microdistribution of NPs in the tissue. By intraarterial injection of carboxyl QDs it was demonstrated that perivascular and tissue-resident macrophages are interconnected by microtubule-containing tubular membranous structures, so-called membrane nanotubes (MNTs). Inside these MNTs, carboxyl QDs are exclusively contained in vesicles, which are transported along the microtubules by molecular motors. Taken together, this thesis elucidates the extra-, intra-, and intercellular distribution of QDs at the microscopic tissue scale. The choice of surface modification critically influences the microdistribution, which should be considered for the future design of NPs that are intended for the use in biomedical applications. Furthermore, it is important to keep in mind that the distribution of NPs in the tissue takes place via different routes including the transport via networks of cells interconnected by MNTs.In der biomedizinischen Forschung werden diverse Nanopartikel (NP) für klinische Anwendungen, die von Diagnostik bis Therapie reichen, entwickelt. Dabei werden die einzigartigen physikalisch-chemischen Eigenschaften sowie die große Vielseitigkeit der NP genutzt. Für jede Anwendung ist es essentiell, dass die NP im Körper ihr Ziel erreichen, z.B. einen bestimmten Zelltyp oder eine spezifische Unterstruktur in einem Organ. Daher war das Ziel dieser Dissertation, die Mikrodistribution von Quantenpunkten (quantum dots, QDs) in Muskelgewebe von gesunden Mäusen zu untersuchen. Um den Einfluss der Oberflächenmodifikation auf die Verteilung im Gewebe zu erforschen, wurden QDs mit Polyethylenglycol (PEG)- oder Carboxyl- Oberflächengruppen verwendet. Kapitel 2 [Nekolla et al., 2016] zeigt mit Hilfe von Echtzeit-Fluoreszenzmikroskopie, Partikel-Tracking und Transmissionselektronenmikroskopie, dass die Mikrodistribution von QDs stark von der Oberflächenmodifikation beeinflusst wird. Lokal injizierte Carboxyl-QDs binden an Elemente der Extrazellulärmatrix wie Kollagenfasern und Basalmembranen. Darüberhinaus befinden sich Carboxyl-QDs in endothelialen Caveolae sowie in Zell-Zell-Kontakten zwischen Endothelzellen, was die Translokation in das Gefäßlumen erlaubt. Im Gegensatz dazu tritt nur wenig Interaktion zwischen PEG-QDs und Gewebekomponenten auf, vielmehr diffundieren PEG-QDs hauptsächlich im Interstitium. Die Daten deuten darauf hin, dass Bestandteile der Extrazellulärmatrix je nach QD-Oberflächenmodifikation als selektive Barriere wirken. Kapitel 3 [Rehberg, Nekolla et al., 2016] legt dar, dass Immunzellen einen Anteil an der Mikrodistribution von NP im Gewebe haben. Mithilfe von intraarterieller Injektion von Carboxyl-QDs wurde gezeigt, dass perivaskuläre und gewebsständige Makrophagen durch röhrenförmige Membranstrukturen, sog. membrane nanotubes (MNTs), die Mikrotubuli enthalten, verbunden sind. Carboxyl-QDs befinden sich in den MNTs ausschließlich in Vesikeln, die mit Hilfe von molekularen Motoren entlang der Mikrotubuli transportiert werden. Zusammengefasst erläutert diese Dissertation die extra-, intra- und interzelluläre Verteilung von QDs auf der mikroskopischen Gewebeebene. Die Wahl der Oberflächenmodifikation hat einen entscheidenden Einfluss auf die Mikrodistribution. Dies sollte für die zukünftige Entwicklung von NP für biomedizinische Anwendungen bedacht werden. Darüberhinaus ist es wichtig zu berücksichtigen, dass NP im Gewebe auf unterschiedliche Art und Weise verteilt werden. Dazu zählt auch der Transport in Netzwerken von Zellen, die durch MNTs verbunden sind

Graph-based description of tertiary lymphoid organs at single-cell level

Our aim is to complement observer-dependent approaches of immune cell evaluation in microscopy images with reproducible measures for spatial composition of lymphocytic infiltrates. Analyzing such patterns of inflammation is becoming increasingly important for therapeutic decisions, for example in transplantation medicine or cancer immunology. We developed a graph-based assessment of lymphocyte clustering in full whole slide images. Based on cell coordinates detected in the full image, a Delaunay triangulation and distance criteria are used to build neighborhood graphs. The composition of nodes and edges are used for classification, e.g. using a support vector machine. We describe the variability of these infiltrates on CD3/CD20 duplex staining in renal biopsies of long-term functioning allografts, in breast cancer cases, and in lung tissue of cystic fibrosis patients. The assessment includes automated cell detection, identification of regions of interest, and classification of lymphocytic clusters according to their degree of organization. We propose a neighborhood feature which considers the occurrence of edges with a certain type in the graph to distinguish between phenotypically different immune infiltrates. Our work addresses a medical need and provides a scalable framework that can be easily adjusted to the requirements of different research questions

Hypothesis‐free deep survival learning applied to the tumour microenvironment in gastric cancer

The biological complexity reflected in histology images requires advanced approaches for unbiased prognostication. Machine learning and particularly deep learning methods are increasingly applied in the field of digital pathology. In this study, we propose new ways to predict risk for cancer-specific death from digital images of immunohistochemically (IHC) stained tissue microarrays (TMAs). Specifically, we evaluated a cohort of 248 gastric cancer patients using convolutional neural networks (CNNs) in an end-to-end weakly supervised scheme independent of subjective pathologist input. To account for the time-to-event characteristic of the outcome data, we developed new survival models to guide the network training. In addition to the standard H&amp;E staining, we investigated the prognostic value of a panel of immune cell markers (CD8, CD20, CD68) and a proliferation marker (Ki67). Our CNN-derived risk scores provided additional prognostic value when compared to the gold standard prognostic tool TNM stage. The CNN-derived risk scores were also shown to be superior when systematically compared to cell density measurements or a CNN score derived from binary 5-year survival classification, which ignores time-to-event. To better understand the underlying biological mechanisms, we qualitatively investigated risk heat maps for each marker which visualised the network output. We identified patterns of biological interest that were related to low risk of cancer-specific death such as the presence of B-cell predominated clusters and Ki67 positive sub-regions and showed that the corresponding risk scores had prognostic value in multivariate Cox regression analyses (Ki67&amp;CD20 risks: hazard ratio (HR) = 1.47, 95% confidence interval (CI) = 1.15-1.89,p= 0.002; CD20&amp;CD68 risks: HR = 1.33, 95% CI = 1.07-1.67,p= 0.009). Our study demonstrates the potential additional value that deep learning in combination with a panel of IHC markers can bring to the field of precision oncology.</p

Label-free determination of hemodynamic parameters in the microcirculaton with third harmonic generation microscopy.

Determination of blood flow velocity and related hemodynamic parameters is an important aspect of physiological studies which in many settings requires fluorescent labeling. Here we show that Third Harmonic Generation (THG) microscopy is a suitable tool for label-free intravital investigations of the microcirculation in widely-used physiological model systems. THG microscopy is a non-fluorescent multi-photon scanning technique combining the advantages of label-free imaging with restriction of signal generation to a focal spot. Blood flow was visualized and its velocity was measured in adult mouse cremaster muscle vessels, non-invasively in mouse ear vessels and in Xenopus tadpoles. In arterioles, THG line scanning allowed determination of the flow pulse velocity curve and hence the heart rate. By relocating the scan line we obtained velocity profiles through vessel diameters, allowing shear rate calculations. The cell free layer containing the glycocalyx was also visualized. Comparison of the current microscopic resolution with theoretical, diffraction limited resolution let us conclude that an about sixty-fold THG signal intensity increase may be possible with future improved optics, optimized for 1200-1300 nm excitation. THG microscopy is compatible with simultaneous two-photon excited fluorescence detection. It thus also provides the opportunity to determine important hemodynamic parameters in parallel to common fluorescent observations without additional label

Graph-based description of tertiary lymphoid organs at single-cell level.

Our aim is to complement observer-dependent approaches of immune cell evaluation in microscopy images with reproducible measures for spatial composition of lymphocytic infiltrates. Analyzing such patterns of inflammation is becoming increasingly important for therapeutic decisions, for example in transplantation medicine or cancer immunology. We developed a graph-based assessment of lymphocyte clustering in full whole slide images. Based on cell coordinates detected in the full image, a Delaunay triangulation and distance criteria are used to build neighborhood graphs. The composition of nodes and edges are used for classification, e.g. using a support vector machine. We describe the variability of these infiltrates on CD3/CD20 duplex staining in renal biopsies of long-term functioning allografts, in breast cancer cases, and in lung tissue of cystic fibrosis patients. The assessment includes automated cell detection, identification of regions of interest, and classification of lymphocytic clusters according to their degree of organization. We propose a neighborhood feature which considers the occurrence of edges with a certain type in the graph to distinguish between phenotypically different immune infiltrates. Our work addresses a medical need and provides a scalable framework that can be easily adjusted to the requirements of different research questions

Intravital THG imaging of blood flow in the mouse cremaster muscle.

<p>Images were scanned with lines from top to bottom and line addition from right to left. Arrows indicate direction of blood flow. All scale bars 20 µm. (a) Combined SHG (red) and THG (cyan) image with mirror-enhanced signals <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0099615#pone.0099615-Rehberg2" target="_blank">[29]</a>. In the left vessel, RBCs flow with the direction of added scan lines, therefore some are elongated to intense streaks. Image brightness was adjusted to allow simultaneous visualization of low and high intensities with a gamma value of 2. (b) Flow in this capillary was with the scan direction from right to left, therefore RBCs appear elongated. (c) Flow in this capillary was against scan direction, from left to right, RBCs therefore appear much shorter (compare scale bars). (d) RBCs flowing in a ∼25 µm vessel. RBC shapes in the image are optically deformed by the relation of blood flow velocity and the scanning process (see main text). (e) THG recording of RBCs suitable for blood flow velocity measurement. Scheme on top illustrates the principle with scanlines 0–3, see Methods for details. In the example shown scan speed was 800 lines per second, the temporal distance between two lines was thus 1.25 ms. Pixel size was 0.31 µm. Blood flow velocity was determined to be 0.75 mm/s.</p

THG microscopy in the mouse ear.

<p>(a,b) Intravital imaging in different animals with arteriole (A), venule (V) and nerve fiber (N) running in parallel. In addition to the THG signal (cyan) SHG (red) is displayed. The arrow points to a typical linear vessel wall signal found only in arterioles. Scale bars 20 µm. The declining THG signal strength in more axial parts of a vessel are easiest to recognize in the arteriole in (a) and the venule in (b). (c–e) Flow velocity profile measurements by THG shifted line scan in the venule shown in b. (c) Clippings from x-t-representations of 12 parallel scan lines spaced 4.4 µm from each other. Lines 1, 11 and 12 were located in the vessel wall and thus show no movement. Note the shallower angles (faster velocity) and decreased intensity in the central scans. (d) Measurements derived from c by manual evaluation of individual streaks (circles) with mean values (horizontal lines) and mean values from LS-PIV calculations (diamonds). Scan lines 2 (0 µm) to 10 (35.2 µm) from (c) are included. Manually measured velocities revealed significant differences between the scan lines (p<0.0001, ANOVA) with significant differences between all direct neighbors (p<0.05 or smaller, post hoc Newman-Keuls test). For scan line 2 (0 µm), only a part of the x-t-representation showed blood flow. Apparently this line was close to the vessel wall so that slight movement could shift it outside. No reasonable LS-PIV average could thus be obtained. LS-PIV evaluations of the other scan lines confirmed significantly different blood flow velocities in general (p<0.0001; ANOVA, n = 88 for each line) and for all direct neighbors (****), except for the two central lines. (e) Measurements by manual evaluation for the arteriole shown in (b) Velocity measurements were significantly different between 0 and 4.4 µm lines (p = 0.0075) and between 8.8 and 13.2 µm lines (p = 0.0129). (f) LS-PIV results for the same arteriole. Only systolic maxima and diastolic minima (circles) and the mean values over all 3.2-millisecond-spaced 179 measurements (line) are shown. In the first scan line systole and diastole could not be identified reliably, therefore only the mean is given. Velocity differences between neighboring scan lines were all significant (p<0.0001) except between 13.2 and 17.6 µm (p = 0.87).</p

THG line scanning in the mouse cremaster muscle.

<p>(a) Scheme of the process. Erythrocytes passing by cause a signal in each of the four sequentially scanned lines, recorded at time points T₁ to T₄. Lines are put together in an x-t-representation (bottom). Here, each erythrocyte moving along the scanned line shows a continuously advancing position, resulting in a streak of signal with a measurable angle. The orientation of the individual lines is the same in all following x-t-representations. (b) x-t-representation from a capillary, (c–f): Comparison of various evaluations on the same 30 µm cremaster venule. (c) x-t-representation. (d) Fourier-transformation of the x-t-representation which is partly shown in c. The calculated average velocity in this example was 1.5 mm/s. (e) Comparison of velocities measured with THG line scan visualized in C (1.56 mm/s±0.22 s.d.) and with fluorescent beads and a camera (1.65 mm/s±0.50 s.d., <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0099615#pone.0099615.s001" target="_blank">Figure S1</a>) in the same venule. Horizontal lines indicate mean values. Double line scans (ds) scanned two parallel lines alternately, with ds-cen more centrally (1.56 mm/s±0.17) and ds-per more peripherally (1.41 mm/s±0.12). Note higher velocity in ds-cen (p = 0.037, t-test). (f) LS-PIV measurements with the line scanning data set visualized in C. Two of seven seconds continuous run are shown with a data point every 16 ms. Average speed was 1.3 mm/s±0.07 s.d. The inset shows the position of the scan line (red) in this venule, visualized by THG. (g) LS-PIV measurements at the center of a 50 µm arteriole from the same cremaster muscle with a data point every 3 ms. Mean velocity over 11.9 seconds (19895 data points) was 2.35 mm/s, heart rate was ∼250 beats/min.</p

Photoswitchable Inhibitors of Microtubule Dynamics Optically Control Mitosis and Cell Death

SummarySmall molecules that interfere with microtubule dynamics, such as Taxol and the Vinca alkaloids, are widely used in cell biology research and as clinical anticancer drugs. However, their activity cannot be restricted to specific target cells, which also causes severe side effects in chemotherapy. Here, we introduce the photostatins, inhibitors that can be switched on and off in vivo by visible light, to optically control microtubule dynamics. Photostatins modulate microtubule dynamics with a subsecond response time and control mitosis in living organisms with single-cell spatial precision. In longer-term applications in cell culture, photostatins are up to 250 times more cytotoxic when switched on with blue light than when kept in the dark. Therefore, photostatins are both valuable tools for cell biology, and are promising as a new class of precision chemotherapeutics whose toxicity may be spatiotemporally constrained using light